A phenomenographic approach on teacher conceptions of teaching Artificial Intelligence (AI) in K-12 schools

A phenomenographic approach on teacher conceptions of teaching Artificial Intelligence (AI) in K-12 schools

• Yau, King Woon Chinese University of Hong Kong
• Chai, C. S. Chinese University of Hong Kong
• Chiu, Thomas K. F. Chinese University of Hong Kong
• Meng, Helen Chinese University of Hong Kong
• King, Irwin Chinese University of Hong Kong
• Yam, Yeung Chinese University of Hong Kong

Education and Information Technologies, (0), -, 2022

Springer

2022

• G 課程與教學:個別教學範疇
  • GD 科學及科技
    • GDA 教學目標、課程及評鑑

Artificial Intelligence (AI) Education K-12 School Education Teacher Conceptions Phenomenography Teacher Professional Development

• Hong Kong

• 1997.7 onwards

• 中學教育

• View Full Text 全文連結

Artificial intelligence (AI) education for K-12 students is an emerging necessity, owing to the rapid advancement and deployment of AI technologies. It is essential to take teachers' perspectives into account when creating ecologically valid AI education programmes for K-12 settings. However, very few studies investigated teacher perception of AI education. Phenomenography is an empirical research method that was widely used to understand teacher's interpretive understanding of new phenomenon, in this study, the teaching of AI in secondary school. Therefore, the present study investigated teachers' conceptions of teaching AI using a phenomenographic approach. Twenty-eight in-service teachers from 17 secondary schools in Hong Kong were invited to participate in an interview after implementing an AI curriculum. Six categories of teacher conceptions were identified: (1) technology bridging, (2) knowledge delivery, (3) interest stimulation, (4) ethics establishment, (5) capability cultivation, and (6) intellectual development. The hierarchical relationships of the six concepts were organised as an outcome space. The space shows a range of surface to deep conceptions and offers an understanding of how teachers perceive AI education through their teaching experience. Two learning paths have been suggested for cultivating technical and non-technical teachers for teaching AI. These learning paths provide insights for teacher educators and policymakers to enhance teachers' competence in teaching AI and promote general AI education for K-12 students. Copyright © 2022 Springer.

• 英文

期刊論文

• 13602357

• 10.1007/s10639-022-11161-x

https://bibliography.lib.eduhk.hk/tc/bibs/b83ef0be

2023-05-08